Higher Accuracy of Lung Ultrasound over Chest X-ray for Early Diagnosis of COVID-19 Pneumonia

Background: The COVID-19 pandemic rapidly strained healthcare systems worldwide. The reference standard for diagnosis is a positive reverse transcription polymerase chain reaction (RT-PCR) test, but results are not immediate and sensibility is variable. Aim: To evaluate the diagnostic accuracy of lung ultrasound compared to chest X-ray for COVID-19 pneumonia. Design and Setting: A retrospective analysis of symptomatic patients admitted into one primary care centre in Spain between March and September 2020. Method: Patients’ chest X-rays and lung ultrasounds were categorized as normal or pathologic. RT-PCR confirmed COVID-19 infection. Pathologic lung ultrasound images were further categorized as showing either local or diffuse interstitial disease. McNemar and Fisher tests were used to compare diagnostic accuracy. Results: Most of the 212 patients presented fever at admission, either as a standalone symptom (37.74% of patients) or together with others (72.17% of patients). The positive predictive value of the lung ultrasound was 90% for the diffuse interstitial pattern and 46.92% for local pattern. The lung ultrasound had a significantly higher sensitivity (82.75%) (p < 0.001), but lower specificity (71%) than the chest X-ray (54.02% and 86%, respectively) (p = 0.008) for identifying interstitial lung disease. Moreover, sensitivity of the lung ultrasound for severe interstitial disease was 100%, and was significantly higher than the chest X-ray (58.33%) (p = 0.002). Conclusion: The lung ultrasound is more accurate than the chest X-ray for identifying patients with COVID-19 pneumonia and it is especially useful for those presenting diffuse interstitial disease.

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ANALYZING CHEST X-RAY TO DIFFERENTIATE SYMPTOMS OF COVID-19 THROUGH ML APPROACH

International Journal of Engineering Applied Sciences and Technology ◽

10.33564/ijeast.2021.v05i12.042 ◽

2021 ◽

Vol 5 (12) ◽

Author(s):

Deepali R Deshpande ◽

Raj L Shah ◽

Anish N Shaha

Keyword(s):

Machine Learning ◽

Learning Model ◽

Time Constraints ◽

X Rays ◽

Rt Pcr ◽

X Ray ◽

Social Distancing ◽

Machine Learning Model ◽

Chest X Ray

The motive behind the project is to build a machine learning model for detection of Covid-19. Using this model, it is possible to classify images of chest x-rays into normal patients, pneumatic patients, and covid-19 positive patients. This CNN based model will help drastically to save time constraints among the patients. Instead of relying on limited RT-PCR kits, just a simple chest x-ray can help us determine health of the patient. Not only we get immediate results, but we can also practice social distancing norms more effectively.

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Chest X-Ray findings and visual quantitative assessment of COVID-19 pneumonia

10.21203/rs.3.rs-32480/v1 ◽

2020 ◽

Author(s):

Michaela Cellina ◽

Marcello Orsi ◽

Marta Panzeri ◽

Giulia van der Byl ◽

Giancarlo Oliva

Keyword(s):

Severity Score ◽

Quantitative Assessment ◽

X Rays ◽

Imaging Findings ◽

Rt Pcr ◽

Disease Evolution ◽

X Ray ◽

Radiological Score ◽

Chest X Ray

Abstract AimTo assess the most common chest X-Ray findings and distribution in patients with confirmed diagnosis of COVID-19; to verify the repeatability of a radiological severity score, based on visual quantitative assessment; to assess the evolution of chest X-Ray findings at follow-up; to evaluate chest X-Ray sensitivity.MethodsWe analysed chest X-Rays at baseline of 110 consecutive COVID-19 patients (79 males, 31 females; mean age: 64±16 years) with RT-PCR confirmation, who presented to our ED.Two radiologists evaluated the imaging findings and distribution.A severity score, based on the extension of lung abnormalities, was assigned by two other radiologists, independently, to the baseline and follow-up X-Rays, executed in 77/110 cases; interobserver agreement was calculated. Chest X-Ray sensitivity was assessed, with RT-PCR as gold standard.ResultsInterobserver agreement was excellent for baseline and follow-up X-Rays (Cohen's K=0.989, p<0.001, Cohen's K=0.985, p<0.001, respectively). The mean score at baseline was 2.87±1.7 for readers 1 and 2. We observed radiological worsening in 52/77 (67%) patients, with significantly higher scores at follow-up (mean score: 4.27±2.15 for reader 1 and 4.28±2.14 for reader 2, respectively); p<0.001.Ground glass opacities were the most common findings (97/110, 88%). Abnormalities showed bilateral involvement in 67/110 (61%), with prevalent peripheral distribution (48/110, 43.5%).The X-Ray sensitivity for the detection of COVID-19 infection was 91%.ConclusionChest X-Ray highlighted imaging findings in line with those previously reported for chest CT. The use of a radiological score can result in clearer communication with Clinicians and a more precise assessment of disease evolution.

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Lung Ultrasound as a New Technique for Diagnosis of Neonatal Respiratory Diseases

Neonatal Network The Journal of Neonatal Nursing ◽

10.1891/0730-0832.37.4.224 ◽

2018 ◽

Vol 37 (4) ◽

pp. 224-232 ◽

Cited By ~ 1

Author(s):

Yasser N. Elsayed

Keyword(s):

Lung Disease ◽

Lung Ultrasound ◽

Point Of Care ◽

Point Of Care Ultrasound ◽

Ultrasound Images ◽

X Ray ◽

The Past ◽

Neonatal Lung ◽

Chest X Ray ◽

A New Technique

Point-of-care ultrasound in the NICU is becoming more commonplace and is now used for a number of indications. Over the past ten years, the use of ultrasound as an alternative to a chest x-ray for the diagnosis of neonatal lung disease has been explored, and protocols were developed to refine the interpretation of ultrasound images in neonatal lung disease. The purpose of this column is to briefly explain the physics of ultrasound and describe the application of ultrasound to neonatal lung assessment.

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Effects of Practice on Detection of Abnormalities in Chest X-Rays

Proceedings of the Human Factors Society Annual Meeting ◽

10.1177/154193128603000325 ◽

1986 ◽

Vol 30 (3) ◽

pp. 309-311

Author(s):

Raja Parasuraman

Keyword(s):

Diagnostic Accuracy ◽

X Rays ◽

X Ray ◽

Disease Identification ◽

Optimal Criterion ◽

Chest X Ray ◽

Radiology Residents ◽

Diagnostic Setting

The performance of radiology residents and staff radiologists in detecting and identifying abnormalities in chest x-rays was examined. 120 chest films were each read five times on five different sessions by each radiologist. Half of the films contained up to eight possible types of abnormality. Practice improved the detectability of abnormalities, as indexed by ROC-based measures, in both groups of readers. However, greater benefits of practice were noted for the residents than for the staff. Staff radiologists, but not the residents, had reporting criteria that were close to the optimal criterion for the diagnostic setting. Accuracy of disease identification also improved with practice in both groups. The results indicate that training and practice can lead to the stabilization of reporting criteria and improvement of diagnostic accuracy in chest x-ray diagnosis.

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Family medicine residents’ skill levels in emergency chest X-ray interpretation

BMC Family Practice ◽

10.1186/s12875-021-01390-3 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Malak Al Shammari ◽

Ali Hassan ◽

Nouf AlShamlan ◽

Sarah Alotaibi ◽

Manar Bamashmoos ◽

...

Keyword(s):

Family Medicine ◽

Diagnostic Accuracy ◽

General Practitioners ◽

Diagnostic Radiology ◽

X Rays ◽

Diagnostic Confidence ◽

X Ray ◽

Chest X Ray ◽

Radiology Residents ◽

Family Medicine Residents

Abstract Background Family medicine physicians may encounter a wide variety of conditions, including acute and urgent cases. Considering the limited access to diagnostic investigations in primary care practice, chest X-ray remains the imaging modality of choice. The current study assessed the competency of family medicine residents in the interpretation of chest X-rays for emergency conditions and to compare it with that of diagnostic radiology residents, general practitioners, and medical interns. Methods An online survey was distributed to 600 physicians, including family medicine residents, medical interns, general practitioners, and diagnostic radiology residents. The study included some background information such as gender, years in practice, training type, interest in pulmonary medicine and diagnostic radiology, and having adequate training on the interpretation of chest X-rays. The survey had 10 chest X-ray cases with brief clinical information. Participants were asked to choose the most likely diagnosis and to rate their degree of confidence in the interpretation of the chest X-ray for each case. Results The survey was completed by 205 physicians (response rate = 34.2%). The overall diagnostic accuracy was 63.1% with a significant difference between family medicine and radiology residents (58.0% vs. 90.5%; P < 0.001). The COVID-19 pneumonia (85.4%) and pneumoperitoneum (80.5%) cases had the highest diagnostic accuracy scores. There was a significant correlation between the diagnostic confidence and accuracy (rs = 0.39; P < 0.001). Multivariable regression analysis revealed that being diagnostic radiology residents (odds ratio [OR]: 13.0; 95% confidence interval [CI]: 2.5–67.7) and having higher diagnostic confidence (OR: 2.2; 95% CI: 1.3–3.8) were the only independent predictors of achieving high diagnostic accuracy. Conclusion The competency of family medicine residents in the interpretation of chest X-ray for emergency conditions was far from optimal. The introduction of radiology training courses on emergency conditions seems imperative. Alternatively, the use of tele-radiology in primary healthcare centers should be considered.

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Lung Ultrasound in COVID-19 pandemic: Why? How? And When?

Likarska sprava ◽

10.31640/jvd.5-6.2020(1) ◽

2020 ◽

pp. 3-12

Author(s):

Khrystyna Pronyuk ◽

Andriy Vysotskyi

Keyword(s):

Critically Ill ◽

Computer Tomography ◽

Critically Ill Patients ◽

Clinical Decision Making ◽

Lung Ultrasound ◽

Clinical Decision ◽

X Rays ◽

Lung Involvement ◽

X Ray ◽

Chest X Ray

During COVID-19 pandemic Lung ultrasound has rapidly become a tool for diagnosis and monitoring of lung involvement and it’s severity. Accurate evaluation of lung pathologic entities at the bedside, especially in critically ill patients, and those on mechanical ventilation, remains problematic. CT should not be frequently repeated and is not available everywhere, especially for critically ill patients. Limitations of bedside chest X-ray have been well described and lead to poor-quality X-ray films with low sensitivity.The lung ultrasound has been shown to be a useful tool in intensive care patients with adult respiratory distress syndrome (ARDS) and can be used forassessing severity of lung involvement in COVID-19. In this paper the accuracy of bedside LUS, chest X-ray and computer tomography are compared based on clinical cases, typical for COVID-19 lung ultrasound appearance is evaluated. There have been shown that lung ultrasound can predict the deterioration of the patient's conditionand can be used for risk stratification and clinical decision making, reducethe use of both chest x‐rays and computer tomography, what is very important especially in limited resources settings.

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Effective Survey on Detection and Classification of COVID-19 Suspected Individual Using CT scan Images

International Journal of Scientific Research in Computer Science Engineering and Information Technology ◽

10.32628/cseit217339 ◽

2021 ◽

pp. 294-299

Author(s):

Snehal R. Sambhe ◽

Dr. Kamlesh A. Waghmare

Keyword(s):

Ct Scan ◽

X Rays ◽

Rt Pcr ◽

X Ray ◽

Feature Extractor ◽

Chest X Ray ◽

Coronavirus Infection ◽

Aided Diagnosis ◽

Excessive Risk

As insufficient testing kits are available, the development of new testing kits for detecting COVID remains an open vicinity of research. It’s impossible to test each and every patient suffering from coronavirus symptoms using the traditional method i.e. RT-PCR. This test requires more time to produce results and have less sensitivity. Detecting feasible coronavirus infection using chest X-Ray may also assist quarantine excessive risk sufferers while testing results are disclosed. A learning model can be built based on CT scan images or Chest X-rays of individuals with higher accuracy. This paper represents a computer-aided diagnosis of COVID 19 infection bases on a feature extractor by using CNN models.

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Comparison of Lung Ultrasound to X-ray for Diagnosis of Pulmonary Complications after Cardiac Surgery in Children

Journal of Nepal Health Research Council ◽

10.33314/jnhrc.v18i1.2236 ◽

2020 ◽

Vol 18 (1) ◽

pp. 47-51

Author(s):

Smriti Mahaju Bajracharya ◽

Pragati Shrestha ◽

Apurb Sharma

Keyword(s):

Cardiac Surgery ◽

Positive Predictive Value ◽

Diagnostic Accuracy ◽

Negative Predictive Value ◽

Predictive Value ◽

Lung Ultrasound ◽

Pulmonary Complications ◽

Lung Ultrasonography ◽

X Ray ◽

Chest X Ray

Background: The purpose of this study was to compare diagnostic performance of lung ultrasound in comparison to chest X-ray to detect pulmonary complication after cardiac surgery in children.Methods: A prospective observational study was conducted in tertiary center of Nepal. 141 consecutive paediatric patients aged less than 14 years scheduled for cardiac surgery were enrolled during the 6 months period. Ultrasound was done on the first post-operative day of cardiac surgery and compared to chest X-ray done on the same day to detect pleural effusion, consolidation, atelectasis and pneumothorax.Results: Sensitivity, specificity, positive and negative predictive values and diagnostic accuracy were calculated using standard formulas. lung ultrasonography had overall sensitivity of 60 %, specificity of 72.4%, positive predictive value of 31.9% and negative predictive value of 89.3% and diagnostic accuracy of 70.2% for diagnosing consolidation. Similarly, lung ultrasonography had overall sensitivity of 90%, specificity of 82.6%, positive predictive value of 46.1% and negative predictive value of 98% and diagnostic accuracy of 83.6 % for diagnosing pleural effusion. For atelectasis, ultrasonography had sensitivity of 50%, specificity of 76.9%, positive predictive value of 30.7% and negative predictive value of 88.2% and diagnostic accuracy of 72.3%. No pneumothoraxes were detected during our study period. Conclusions: Lung ultrasound is an alternative non-invasive technique which is able to diagnose pulmonary complications after cardiac surgery with acceptable diagnostic accuracy with no proven complications but with decreasing exposure to ionizing radiation and possibly cost.Keywords: Cardiac surgery; children; lung ultrasound; pulmonary complications

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Cohort Study: The Accuracy of Screening Methods of COVID-19 in Pregnancy: Practical Approach in Low Resources Health Services

10.1101/2021.09.20.21263866 ◽

2021 ◽

Author(s):

Muhammad Ilham Aldika Akbar ◽

Khanizyah Erza Gumilar ◽

Eccita Rahestyningtyas ◽

Manggala Pasca Wardhana ◽

Pungky Mulawardhana ◽

...

Keyword(s):

Diagnostic Accuracy ◽

Pregnant Women ◽

Antibody Test ◽

Screening Methods ◽

Rt Pcr ◽

Predictive Values ◽

X Ray ◽

Low Middle Income Countries ◽

Chest X Ray ◽

Rapid Antibody

Background All pregnant women in labor should be universally screened for Coronavirus Disease 2019 (COVID-19) during pandemic periods using Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) test. In many low-middle income countries, screening method was developed as an initial examination because of limited availability of RT-PCR tests. Objectives This study aims to evaluate the screening methods of COVID-19 accuracy in pregnant women. Material and Methods We recruited all pregnant women with suspicion of COVID-19 from April - August 2020 at Universitas Airlangga hospital, Surabaya, Indonesia. The participant was divided into two groups based on RT-PCR results: COVID-19 and non-COVID-19 group. The proportion of positive signs & symptoms, rapid antibody test, abnormal findings in chest x-ray, and neutrophil to lymphocyte ratio (NLR) value were then compared between both groups. The sensitivity, specificity, positive predictive value (PPV), negative predictive values (NPV), and diagnostic accuracy (DOR) were calculated. Results A total 141 pregnant women with suspected COVID-19 cases were recruited for this study. This consist of 62 COVID-19 cases (43.9%) and 79 non COVID-19 pregnant women (56.1%). The sensitivity, spesificity, PPV, NPV, and diagnostic accuracy of each parameter are as follow: clinical sign & symptoms (24.19%, 75.95%, 3.92%, 96.11%, 65.87%), rapid antibody test (72.73%, 35.06%, 4.35%, 96.94%, 36.53%), chest x-ray (40.68%, 59.45%, 3.92%, 96.11%, 58.76%), and NLR > 5.8 (41.38%, 72%, 5.66%, 96.80%, 70.81%). Conclusions The use of combined screening methods can classify pregnant women with high-risk COVID-19 before definitively diagnosed with RT-PCR. This practice will help to reduce RT-PCR need in a limited resources country.

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Chest X-Rays Findings in Patients Positive for COVID 19 at Sheikh Zayed Hospital Lahore

10.53350/pjmhs211551196 ◽

2021 ◽

Vol 15 (5) ◽

pp. 1196-1199

Author(s):

A. Z. Sheikh ◽

Z. Tariq ◽

S. Noor ◽

A. Ambreen ◽

S. Awan ◽

...

Keyword(s):

Ground Glass Opacity ◽

British Society ◽

Ground Glass ◽

Care Hospital ◽

X Rays ◽

Middle Zone ◽

Rt Pcr ◽

Thoracic Imaging ◽

X Ray ◽

Chest X Ray

Aim: To assess the results of chest x ray radiographs of patients positive for Covid-19, presented at the tertiary care hospital according to the classification by the British Society of Thoracic Imaging (BSTI. Place and Duration: In COVID-19 Ward (Department of Medicine) Sheikh Zayed Hospital, Lahore for three months duration from January 2021 to March 2021. Methods: A total of 96 patients were selected. In this observational study, positive COVID-19 patient determined by the reverse transcriptase polymerase chain reaction (RT-PCR) were enrolled for this study above the age of 14 years. CXR results were classified conferring to BSTI documentation and classification in terms of percentage and frequency. Results: Chest rays of 96 patients who tested positive for Covid-19 by RT-PCR over the age of 14 years were examined. Chest X-rays are classified according to the BSTI Covid-19 X-ray classification. Out of 96 patients, 10 patients (10.41%) had normal chest x-rays, 19 (19.80%) patients had classic bilateral, peripheral and basal consolidation / ground glass opacity (GMO), 60 (62.5%) had unspecified group,7(7.29%) patients have poor quality X-ray film. The unilateral involvement was noticed in 15 and bilateral in 49 patients, 12 of the patients had diffuse involvement on chest radiograph and peripheral involvement in 39 patients. According to regional dominance, 41 of the unspecified (42.70%) had middle and lower lung involvement, 7 (7.29%) had only the middle zone, and 8 (8.33%) had involvement of lower zone. Conclusions: In this study, Covid-19 chest X-rays are usually presented as ground glass opacity, mixed consolidation with GGOs in the middle and lower peripheral areas of the bilateral lung. Chest X-ray BSTI classification is used to classify Covid-19 severity in our patients, thus differentiating in the classic Covid-19 of the middle zone versus low zone involvement. Keywords: Consolidation, Covid, Ground Glass Opacity, Chest Image.

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